Detailed mapping of behavior reveals the formation of prelimbic neural ensembles across operant learning

Yan Zhang, Alexander J. Denman, Bo Liang, Craig T. Werner, Nicholas J. Beacher, Rong Chen, Yun Li, Yavin Shaham, Giovanni Barbera, Da Ting Lin

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

The prelimbic cortex (PrL) is involved in the organization of operant behaviors, but the relationship between longitudinal PrL neural activity and operant learning and performance is unknown. Here, we developed deep behavior mapping (DBM) to identify behavioral microstates in video recordings. We combined DBM with longitudinal calcium imaging to quantify behavioral tuning in PrL neurons as mice learned an operant task. We found that a subset of PrL neurons were strongly tuned to highly specific behavioral microstates, both task and non-task related. Overlapping neural ensembles were tiled across consecutive microstates in the response-reinforcer sequence, forming a continuous map. As mice learned the operant task, weakly tuned neurons were recruited into new ensembles, with a bias toward behaviors similar to their initial tuning. In summary, our data suggest that the PrL contains neural ensembles that jointly encode a map of behavioral states that is fine grained, is continuous, and grows during operant learning.

Original languageEnglish
Pages (from-to)674-685.e6
JournalNeuron
Volume110
Issue number4
DOIs
StatePublished - 16 Feb 2022
Externally publishedYes

Keywords

  • behavioral sequence
  • behavioral tuning
  • cognitive maps
  • deep behavior mapping
  • learning
  • longitudinal calcium imaging
  • miniScope
  • neural ensembles
  • operant conditioning
  • prelimbic cortex

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